access icon free Robust predictive filtering schemes for sub-band CQI feedback compression in 3GPP LTE systems

© The Institution of Engineering and Technology
Received 14/02/2017, Accepted 02/05/2017, Revised 19/04/2017, Published 12/05/2017

The third generation partnership project (3GPP) long-term evolution (LTE) cellular system offers high data rate capabilities by leveraging several techniques including link adaptation and frequency selective scheduling. These techniques rely on accurate channel quality indicator (CQI) feedback reports that are sent by the user equipment (UE) to the evolved node B, a process which results in high signalling overhead. In this study, the authors propose a UE-assisted sub-band feedback compression scheme based on a predictive filtering technique to reduce this signalling overhead. Four schemes based on adaptive filters have been designed, implemented and tested in an LTE system level simulator. Simulation results indicate that the proposed compression scheme has shown efficacy with an overall CQI feedback signalling reduction of up to 92.5% whilst maintaining stable sector throughput, when compared with the standard 3GPP CQI feedback mechanism. Although the proposed scheme exhibits low computational and memory complexity, a reduced-complexity scheme achieving an average computational load reduction of up to 35% is also presented.

Inspec keywords: computational complexity; telecommunication scheduling; filtering theory; wireless channels; Long Term Evolution; 3G mobile communication

Other keywords: channel quality indicator feedback; robust predictive filtering scheme; 3GPP Long-Term Evolution cellular system; overall CQI feedback signalling reduction; signalling overhead reduction; third generation partnership project LTE cellular system; link adaptation; UE-assisted sub-band feedback compression scheme; user equipment; average computational load reduction; subband CQI feedback compression; high signalling overhead; frequency selective scheduling; low computational and memory complexity

Subjects: Mobile radio systems; Filtering methods in signal processing

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